The concentration-response relationship per endpoint and chemical has to be 1-to-1.
If not, use create_dataset() for pre-processing or
use combi_run_rcurvep(), which has both pre-processing and more flexible parameter controls.
Usage
run_rcurvep(
d,
mask = 0,
config = curvep_defaults(),
keep_sets = c("act_set", "resp_set", "fp_set"),
...
)Arguments
- d
Datasets with columns: endpoint, chemical, conc, and resp, mask (optional) Example datasets as zfishbeh. It is required that the baseline of responses in the resp column to be 0.
- mask
Default = 0, for no mask (values in the mask column all 0). Use a vector of integers to mask the responses: 1 to mask the response at the highest concentration; 2 to mask the response at the second highest concentration, and so on. If mask column exists, the setting will be ignored.
- config
Default configurations set by
curvep_defaults().- keep_sets
The types of output to be reported. Allowed values: act_set, resp_set, fp_set. Multiple values are allowed. act_set is the must.
act_set: activity data
resp_set: response data
fp_set: fingerprint data
- ...
Curvep settings. See
curvep_defaults()for allowed parameters. These can be used to overwrite the default values.
Value
An rcurvep object. It has two components: result, config
The result component is also a list of output sets depending on the parameter, keep_sets.
The config component is a curvep_config object.
Often used columns in the act_set: AUC (area under the curve), wAUC (weighted AUC), POD (point-of-departure), EC50 (Half maximal effective concentration), nCorrected (number of corrected points).
Examples
data(zfishbeh)
d <- create_dataset(zfishbeh)
# default
out <- run_rcurvep(d)
# change TRSH
out <- run_rcurvep(d, TRSH = 30)
# mask response at highest and second highest concentration
out <- run_rcurvep(d, mask = c(1, 2))